A comprehensive review on the application of artificial intelligence in drug discovery.

Author:

Sahoo Ashrulochan1,Dar Ghulam Mehdi2

Affiliation:

1. Department of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Bathinda - 151401, Punjab, India

2. Department of Biochemistry, Govind Ballabh Pant Institute of Post-graduate Medical Education and Research, Jawahar Lal Nehru Marg, Rajghat, New Delhi - 110002, Delhi, India

Abstract

The 21st century is witnessing immense achievements in human history, starting from home science to space science. Artificial Intelligence (AI) is a salient one among these feats, the critical factor of the 4th industrial revolution. Health is the primary and essential asset for the continuity of human civilization on this planet. Not only must we address the deadly existing diseases like Cancer, AIDS, Alzheimer's, heart diseases, gastrointestinal diseases, etc., but on top of that, we must effectively predict, prevent and respond to potential pathogens capable of causing havoc like the recent outbreak caused by SARS-CoV-2. AI-enabled technology with the computational capacity of a computer and reasoning ability of humans saves surplus labor and time that is majorly consumed in target validation, lead optimization, molecular representation, and designing reaction pathways, which traditionally is a decade-long way of searching, visualizing, studying, imagining, experimenting and maintaining a ton of data. This article would focus on how AI will help find the drug-like properties in the compound screening phase predicting the Structure-Activity Relationship (SAR) and ADMET properties in lead identification and optimization phases, sustainable development of chemicals in the synthesis phases up to AI's assistance in the successful conduct of clinical trials and repurposing.

Publisher

The Applied Biology & Chemistry Journal

Reference96 articles.

1. Renz P, Hochreiter S, Klambauer G (2019). Uncertainty estimation methods to support decision-making in early phases of drug discovery. In: Workshop on Safety and Robustness in Decision-making at 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada.

2. Berdigaliyev N, Aljofan M (2020). An overview of drug discovery and development. Future Med Chem; 12(10):939-947. https://doi.org/10.4155/fmc-2019-0307

3. Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, et al. (2017). Mastering the game of go without human knowledge. Nature; 550:354-359. https://doi.org/10.1038/nature24270

4. Hsu FH (2002). Behind deep blue: building the computer that defeated the world chess champion. Princeton University Press.

5. Bojarski M, Testa DD, Dworakowski D, Firner B, Flepp B, et al. (2016). End to end learning for self-driving cars. arXiv:1604.07316

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3